What Is CDISC and What Are CDISC Data Standards? | Allucent

What Is CDISC and What Are CDISC Data Standards?

What Is CDISC and What Are CDISC Data Standards

CDISC stands for the “Clinical Data Interchange Standards Consortium,” and is a global not-for-profit organization that actively develops data standards with the collective knowledge and experience of volunteers within the pharmaceutical industry. There are three major standards that CDISC supports which are, SDTM, ADaM, and SEND. The CDISC standards for clinical studies are SDTM and ADaM, while nonclinical studies utilize SEND. This guide provides important information to be aware of when it comes to implementing CDISC data standards in your drug development program.

What Does CDISC Do & Why Is CDISC Important?

CDISC creates and communicates standards that support the acquisition, exchange, submission, and archive of data for medical and biopharmaceutical product development. The consortium works in tandem/collaboration with global agencies like the U.S. Food and Drug Administration (FDA), European Medicines Agency (EMA), Japan’s Pharmaceuticals and Medical Devices Agency (PMDA), and China’s National Medical Products Administration (NMPA) to develop guidelines and requirements that influence the standards for both clinical and nonclinical data. As global regulations are constantly evolving and changing, so do CDISC standards. There are many benefits that CDISC standards provide. Some of the benefits of implementing CDISC data standards include:

  • CDISC standards support transparency in the process of medical research from the protocol phase to the reporting of data and results
  • Implementation of CDISC standards can decrease timelines and costs during drug development by expediting the regulatory processes, leading to a faster marketing authorization
  • CDISC standards reduce the amount of time FDA reviewers spend on data review and allow them to spend more time on the science of drug development
  • When CDISC data standards are implemented, high-quality, interpretable data can be exchanged easily and efficiently between CROs and Sponsors

FDA, NMPA, & PMDA Regulatory Requirements

When are CDISC standards required? The requirements vary between global agencies. There are different CDISC regulatory requirements and important dates to be aware of for each agency. There are no set date requirements for the EMA, however, the FDA, NMPA, and PMDA all have different date requirements for when CDISC is required for submission.

AgencyClinical CDISCNonclinical CDISC
EMANot referencedNot referenced
FDASDTM – CDER & CBER – Required – 12/17/2016* ADAM – CDER & CBER – Required – 03/15/2019*CBER – Required – 03/15/2023 CDER – Required – 12/17/2016*
NMPAPreferred – September 2019No Requirement
PMDASDTM & ADaM – Required – 04/01/2020No Requirement

*Requirements are dependent on type of submission, IND, ANDA, NDA, BLA, etc.

CDISC Data Standards in Clinical Research & Clinical Studies

CDISC datasets help provide reviewing regulatory agencies with clear and standardized clinical trial data. When data is poorly organized or not easily interpretable, this can cause pushback from governing agencies or delays in the drug development process with valuable time being spent organizing and making sense of the data. CDISC data standards provide sponsors efficiency in structuring their raw data in alignment with globally accepted and required standards for successful data submissions. Another way to provide clarity is by implementing Controlled Terminology (CT). CT is an ever-evolving repository of approved terms used to harmonize data collected across studies to a common value for electronic data processing and submission. CT gives straightforward context to data and removes ambiguity in result evaluation.

Pharmacokinetic CDISC Data Standards

Within CDISC, an important subset of clinical trial data is pharmacokinetic (PK) data. Working with PK data is a highly specialized area of CDISC data management. It is critical to understand the differences between the sources and types of PK data collected during a trial as well as how to combine those different data sources in the correct format in order to develop a dataset that can be used in PK analyses. PK and CDISC work together to create a clean and comprehensible clinical trial submission package. As mentioned above, CDISC has three major data standards: SEND for nonclinical data, SDTM for clinical data, and ADaM for analysis ready data. In the PK domains for SDTM and ADaM, clinical and bioanalytical data must be reconciled. PK parameters need to be generated from a separate analysis and specialized domains are created to show the relationship between the bioanalytical data and calculated PK parameters.

CDISC Domains

SEND, SDTM, and ADaM data are all organized into domains. A domain is a collection of related observations pertaining to a specific topic collected for all human subjects or animals in a clinical or nonclinical investigation.

Clinical PK Domain Definitions:

The relevant PK domains for SEND and SDTM are the pharmacokinetic concentrations (PC) domain, the pharmacokinetic parameters (PP) domain, and the related records (RELREC) domain. The relevant PK domains for ADaM are the analysis dataset of pharmacokinetic concentrations (ADPC) and the analysis dataset of pharmacokinetic parameters (ADPP), which are used for PK analyses PC: Data collected for tissue (e.g., serum or plasma) and fluid concentrations of analytes (usually study drugs and/or their metabolites) as a function of time prior to and after dosing the study drug. PP: Data describing the PK parameters of the time-concentration curve for PC data in a standardized format (e.g., the area under the curve, maximum concentration, time of maximum observed concentration sampled during a dosing interval). RELREC: Data that relates the exact PK concentrations from the PC dataset to the resulting PK parameters in the PP dataset. ADPC: Analysis ready data collected for tissue and fluid concentrations of analytes as a function of time. This dataset may contain additional information to the SDTM PC domain, including calculations of elapsed times, analysis flagging, and imputations of values below the lower limit of quantification. ADPP: Analysis-ready data describing the parameters of the time-concentration curve for PC data. This dataset may contain additional information to the SDTM PP dataset, including flags for values to be used in further analyses, such as tables, listings, figures, or bioequivalence/bioavailability analyses.

Nonclinical PK Domain Definitions:

The relevant domains for SEND include the pool definitions (POOLDEF) and the supplemental qualifiers for pharmacokinetic concentration (SUPPPC), as well as the PC and PP domains as described above in the clinical PK domains. POOLDEF: Data to combine and identify individual animals used in a pooled profile for analysis. SUPPPC: Supplementary dataset which provides additional qualifiers that cannot be captured within PC variables.

SEND

SEND stands for “Standard for the Exchange of Nonclinical Data.” SEND guides the organization, structure, and format of all nonclinical data. The SEND Implementation Guide (SEND-IG) provides predefined domains and examples of nonclinical (animal) data based on the structure and metadata defined by the SDTM. The current SEND-IG version 3.1.1 is designed to support single-dose toxicology, repeat‑dose toxicology, and carcinogenicity studies. Respiratory and cardiovascular testing in safety pharmacology studies are also covered by SEND. Capturing immunogenicity specimen assessment data is still in development.

SDTM

SDTM stands for “Study Data Tabulation Model.” SDTM is arguably the most well-recognized and widely implemented CDISC standard. SDTM outlines a universal standard for how to structure and build content for data sets for individual clinical study data. The SDTM Implementation Guide (SDTM-IG) gives a standardized, predefined collection of domains for clinical data submission, each of which is based on the structure and metadata defined by the SDTM. SDTM data are raw data and often need further modification before the data are analysis-ready.

ADaM

ADaM stands for “Analysis Data Model.” ADaM can also be thought of as data that is “analysis ready.” The main difference between ADaM and SDTM standards is the way in which the data is displayed. SDTM provides a standard for the creation and mapping of collected data from raw sources, whereas ADaM provides a standard for the creation of analysis-ready data, often using SDTM data as the source. ADaM datasets can be used by the FDA to easily recreate analyses.

Are You CDISC Ready?

Allucent is an industry leader in PK CDISC standards. As a CDISC gold member (2021, 2022) our CDISC experts at Allucent are actively involved in all forms of PK CDISC standards and implementation. Make your PK SEND, SDTM, and ADaM datasets work with your CRO to ensure proper implementation of PK CDISC. Allucent can help:

  • Generate PK datasets for legacy, planned, and current studies
  • Generate full CDISC datasets (all domains, SDTM, ADaM with a define.xml)
  • Work with your CRO on CDISC implementation and reconciliation
  • Provide advice for FDA submissions

Contact a member of our expert PK CDISC team to learn more about CDISC and to see if your datasets are in compliance with the FDA’s required CDISC standards.

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